Confidence intervals for large non- centrality parameter
| Contribuinte(s) |
Zmyślony, R. |
|---|---|
| Data(s) |
09/01/2017
09/01/2017
02/05/2015
|
| Resumo |
We use asymptotic linearity to derive confidence intervals for large noncentrality parameters. These results enable us to measure relevance of effects and interactions in multifactors models when we get highly statistically significant the values of F tests statistics. We show how to use our approach by considering two sets of data as application examples. |
| Identificador |
Inácio, S. T., Oliveira, M. M., Mexia, J.T. 2015. Confidence intervals for large non-centrality parameter. Discussiones Mathematicae Probability and Statistics 35.45–56 doi:10.7151/dmps.1175. ISSN 1509-9423,ISSN 2084-0381. 2084-0381 http://hdl.handle.net/10174/19621 S.TimoteoInacio@brighton.ac.uk mmo@uevora.pt jtm@fct.unl.pt 336 doi:10.7151/dmps.1175 |
| Idioma(s) |
eng |
| Publicador |
Discussiones Mathematicae Probability and Statistics |
| Direitos |
restrictedAccess |
| Palavras-Chave | #asymptotic linearity #non-centrality parameters #highly significant F tests #measure relevance |
| Tipo |
article |
